UGV-Conditioned Multi-UAV Informative Planning on a Shared Exposure Belief

Abstract:Safe ground navigation in large, threat-augmented environments requires aerial support that actively reduces the risks that a ground vehicle faces along its route. Existing aerial reconnaissance systems focus on mapping or covering the environment, but do not direct sensing toward regions that are most relevant for ground vehicle safety. In this paper, we address the problem of coordinating a team of unmanned aerial vehicles (UAVs) to improve the safety of an unmanned ground vehicle (UGV) navigating through unknown threat zones. A key aspect of our approach is a risk-averse shared exposure belief for UGV routing and a mission-conditioned UAV reward that directs sensing toward uncertain, exposure-relevant regions of the current UGV corridor. UAV observations update the shared belief online, allowing the UGV to replan around newly revealed threats while the evolving route in turn reshapes UAV sensing priorities. For multiple UAVs, we use region-conditioned spatial assignment to reduce redundant sensing. Simulation experiments show that our approach reduces cumulative UGV exposure by 38% compared with terrain-semantic replanning, and reduces redundant aerial coverage from 38.8% to 3.7% under our multi-UAV coordination scheme.

Robotics (cs.RO)

arXiv:2606.12306 [cs.RO]

(or arXiv:2606.12306v2 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2606.12306 Focus to learn more arXiv-issued DOI via DataCite

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